Browsing by Author "Uddin, Mohammed Nasir"

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Assessing Rural Women's Satisfaction with Public Services in Bangladesh: Case Study of Provision of Public Services by Civil Society Organization.
(Scopus, 2024) Uddin, Mohammed Nasir; Akter, Sanjida; Mahzabin, ffat Ara; Muchemi, Julius Githinji; Akter, Sharmin
Poverty continues to ravage about 10 percent of the world population. Efforts to eradicate poverty in all its forms remain elusive. The historical decline in global poverty rate experienced from 10.1% in 2015 to 8.6% in 2018 and even further down to 8.3% in 2019 reverses to 9.2% in 2019 due to COVID-19 pandemic. Although the poverty rate is projected to decrease to 8.6% in 2022, efforts to lower it further are confounded by the emerging global uncertainties including the Ukraine-Russia war, the global economic crisis, and catastrophes of earthquakes, and adverse effects of climate change. To address poverty in a country, the government and other development actors, including civil society, must establish national definitions, set targets, and conduct assessments on how the poor access and are satisfied with public services. This necessitates an understanding of the poor's socioeconomic circumstances, as well as the factors that influence service providers' ability to meet their expectations. This study was primarily undertaken to determine the satisfaction level of rural women with public services provided through civil society programs within four villages in the northern parts of Bangladesh. It also explores what factors influence the satisfaction level. Findings indicated that highest proportion of the respondents (53%) had a high level of satisfaction. In addition, the findings show that respondents' knowledge of civil society organization services and duration of involvement in civil society organizations, as well as family size, annual family income, and training, were significantly correlated with women's satisfaction with the services provided by civil society organizations. Furthermore, age, family size, annual income, and farm size are important socioeconomic factors that can influence women's satisfaction with public services provided by civil society organizations. It concludes that the selected civil society organization lacks the necessary personnel to provide public services and assess program success. The implication is that for civil societies to successfully supplement the government's public services, they must examine the existing gaps and barriers that need to be addressed in providing the services.
BSEVOTING
(Scopus, 2021) Alvi, Syada Tasmia; Islam, Linta; Rashme, Tamanna Yesmin; Uddin, Mohammed Nasir
In a democratic society, a citizen's ability to vote is regarded as one of the most significant legal rights he or she may exercise. For e-voting methods, blockchain presents new possibilities to properly meet transparency, integrity, anonymity and many other security properties. As the need for blockchains keeps rising, demand for bigger, more scalable, more adaptable, and more cost-effective multipurpose chain is also high. Conventional blockchains are incapable of meeting all of these demands. To solve the problems (mostly performance) associated with main blockchains, sidechain technology has recently evolved as a separate chain connected to the main chain that runs in parallel with transactions. Our proposed method is designed to operate on a public blockchain, but we separate the storage of voting information of each candidate using a sidechain to offer a cost-effective blockchain-based voting mechanism by ensuring the security properties such as anonymity, integrity, privacy, security, fairness, receipt freeness and so many. In future, we will broadly discuss and implement this voting system.
DVTChain
(Daffodil International University, 22-07-01) Alvi, Syada Tasmia; Uddin, Mohammed Nasir; Islam, Linta; Ahamed, Sajib
Voting is a fundamental democratic activity. Many experts believe that paper balloting is the only appropriate method to ensure everyone’s right to vote. But this method is prone to errors and abuse. Many nations utilize digital voting methods to solve the difficulties of paper balloting. A single flaw in digital voting may lead to massive vote-rigging. Election voting methods must be legal, accurate, safe, and convenient. However, issues with digital voting methods may restrict acceptance. Due to its end-to-end verification capabilities, blockchain technology was developed to address these problems. To guarantee We have used blockchain technology anonymity, privacy, verifiability, mobility, integrity, security, and fairness in voting. By using blockchain our proposed system ensures security, privacy, and integrity. This system provides voter anonymity by keeping the voter information as a hash in the blockchain. It also provides fairness by keeping the casted vote encrypted till the ending time of the election. After ending time, the voter can verify their casted vote, ensuring verifiability. To test our protocol, we put it on Ethereum 2.0, a blockchain platform that uses Solidity as a programming language to create smart contracts. The adoption of smart contracts provides a safe means for performing voter verification, ensuring the correctness of voting results, making the counting system public, and protecting against fraudulent activities. We analyzed the system’s performance based on security and gas costs. It improves in terms of security characteristics and the related cost for the necessary infrastructure.
Factors Affecting Rural Women’s Knowledge on Food and Nutrition
(Springer Nature Limited, 2023-04-28) Uddin, Mohammed Nasir; Roy, Purobee; Rahman, Saifur; Al-Amin, Abul Quasem; Wahaj, Zujaja
This study investigates the factors affecting women's knowledge about food and nutrition in selected areas of rural Bangladesh. Respondents of the study included women who had participated in the BRAC Health Nutrition and Population Programme in the study region of Bangladesh in 2017. The findings revealed that women had a good level of knowledge about food and nutrition. Family size, annual income, and degree of education have significant effects on rural women's understanding of food and nutrition. We recommend developing an integrated approach by the government, extension department, and NGOs to work in collaboration within the rural contexts so that the country meets the United Nations Sustainable Development Goal 2: achieving food security and improved nutrition. This research will help policymakers in Bangladesh to devise effective strategies for addressing the country's current challenges of nutrition and associated health risks.
Factors affecting rural women’s knowledge on food and nutrition: a case of specific areas of rural Bangladesh
(2023-04-28) Uddin, Mohammed Nasir; Roy, Purobee; Rahman, Saifur; Al-Amin, Abul Quasem; Wahaj, Zujaja
This study investigates the factors affecting women's knowledge about food and nutrition in selected areas of rural Bangladesh. Respondents of the study included women who had participated in the BRAC Health Nutrition and Population Programme in the study region of Bangladesh in 2017. The findings revealed that women had a good level of knowledge about food and nutrition. Family size, annual income, and degree of education have significant effects on rural women's understanding of food and nutrition. We recommend developing an integrated approach by the government, extension department, and NGOs to work in collaboration within the rural contexts so that the country meets the United Nations Sustainable Development Goal 2: achieving food security and improved nutrition. This research will help policymakers in Bangladesh to devise effective strategies for addressing the country's current challenges of nutrition and associated health risks.
Improving the Accuracy of Heart Disease Prediction Approach of Machine Learning Algorithms
(IEEE, 2023-05-23) Hossain, Md. Belal; Uddin, Mohammed Nasir; Alvi, Syada Tasmia; Era, Chowdhury Abida Anjum
The work is about forecasting heart disease. First and foremost, we gathered data from various sources and divided it into two portions, one of which is 80% and the other is 20%, where the first part is for training and the remainder is reserved for the test dataset. After collecting this dataset, we applied the pre-processing formula and different classifier algorithms. K-Nearest Neighbor, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes & Logistic Regression are the techniques utilized here. When compared to other algorithms, Logistic Regression, KNN, and SVM provided the same or superior accuracy. Precision, Recall, F1 score, and ERR are used to measure accuracy. Gender, Glycogen, BP, and Heartrate are some of the prefixes used while training and found to be different major vulnerable factors of heart diseases. The direction of this work is real-life experiments and clinical trials using different devices.